# Copyright 2025 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# ============================================================================
"""Test contiguous"""
import numpy as np
import mindspore as ms
from tests.mark_utils import arg_mark


@arg_mark(plat_marks=['cpu_linux'], level_mark='level0', card_mark='onecard',
          essential_mark='essential')
def test_large_shape_permute_contiguous():
    """
    Feature: Test contiguous.
    Description: Test permute and contiguous with large Tensor shape.
    Expectation: success.
    """
    input_np = np.ones((382, 1920, 1080, 3), dtype=np.float16)
    x = ms.from_numpy(input_np)
    y = x.permute(0, 3, 1, 2)
    assert np.allclose(y.asnumpy(), np.ascontiguousarray(np.transpose(input_np, (0, 3, 1, 2))))
